Collaborative Research Program in Pharmacometrics and Quantitative Systems Pharmacology

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Interdisciplinary initiatives have been identified as a crucial way to synergize research in the modern era, where the complexity of encountered problematics and questions can rarely be solved through in silo efforts. Moreover, because of the big demand for funds and the societal pressure for reporting on return on investments, innovative solutions are increasingly being driven by needs, whether in fundamental or applied sciences. Transcending boundaries between disciplines is thus becoming a necessity rather than a researcher's whim, especially when it comes to human health issues, where discipline-specific projects can often lack vision and scope. The pharmaceutical field is no exception to this change in the research model, motivated by the underlying complexity of the dose-exposure-effect relationship, further challenged by the pathophysiological aspects involved. The empirical culture, which historically prevailed in this field, is gradually fading to give more ground to complementary or alternative mathematical and computational tools, to rationalize and quantify drug development and use. However, the shortage for experienced drug development scientists in quantitative pharmacology/pharmacometrics, with the multi-facets that this field asks for, is a main limiting factor for its deployment in the pharmaceutical industry. With the objective to provide insights into unmeasured or unmeasurable clinical entities, this collaborative research and development (CRD) program is in reflection of this ever-changing nature in drug R&D, and bases on solid theoretical foundations to provide quantification methodologies that support rational therapeutic decisions for improvement of patient health. It is built on well- identified needs in drug R&D where mathematically founded approaches have significant impact and bring added-value. It encompasses several therapeutic areas, including neurological conditions, oncology and infectious diseases. To ensure transferability to the end-users and society, this research program is organically structured to involve translational aspects, through development of computational and mobile health applications that reflect clinical needs. It is dedicated to train a whole generation of drug modelers.